roi_pooling | four ways to compare the speed of roi pooling in pytorch | Caching library

by SirLPS Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | roi_pooling Summary

roi_pooling is a Python library typically used in Server, Caching applications. roi_pooling has no bugs, it has no vulnerabilities and it has low support. However roi_pooling build file is not available. You can download it from GitHub.

use_cuda: True, has_backward: True method0: 0.0344547653198242, batch_size: 1, size: 50, num_rois: 300 method1: 0.1322056961059570, batch_size: 1, size: 50, num_rois: 300 method2: 0.1307379817962646, batch_size: 1, size: 50, num_rois: 300 method3: 0.2016681671142578, batch_size: 1, size: 50, num_rois: 300.

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Quality

Security

License

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Support

roi_pooling has a low active ecosystem.

It has 61 star(s) with 10 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 0 have been closed. On average issues are closed in 423 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of roi_pooling is current.

Quality

roi_pooling has 0 bugs and 0 code smells.

Security

roi_pooling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

roi_pooling code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

roi_pooling does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

roi_pooling releases are not available. You will need to build from source code and install.

roi_pooling has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed roi_pooling and discovered the below as its top functions. This is intended to give you an instant insight into roi_pooling implemented functionality, and help decide if they suit your requirements.

Forward computation
Get number of blocks used by CUDA
Perform adaptive pooling
Convert a torch variable to a chainer variable
Perform the roi pooling
Perform the backward computation
Backward computation
Core function for roi pooling
Import all symbols

Get all kandi verified functions for this library.

roi_pooling Key Features

No Key Features are available at this moment for roi_pooling.

roi_pooling Examples and Code Snippets

No Code Snippets are available at this moment for roi_pooling.

Community Discussions

Trending Discussions on roi_pooling

How to fix ' ImportError: cannot import name 'numpy_type_map' ' in Python?

Roi pooling and backpropagation

coverting roi pooling in pytorch to nn layer

QUESTION

How to fix ' ImportError: cannot import name 'numpy_type_map' ' in Python?

Asked 2020-Jan-08 at 07:34

I've followed the instructions in Detectron and I've configured it several times: the code compiles as it should. When it comes to run the code, I get this error:

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ANSWER

Answered 2019-Jan-27 at 11:49

I suppose there is a version mismatch between detectron and the needed pytorch release you are using. if you look at latest pytorch source code, there is no numpy_type_map component. https://github.com/pytorch/pytorch/blob/master/torch/utils/data/dataloader.py

Source https://stackoverflow.com/questions/54387659

QUESTION

Roi pooling and backpropagation

Asked 2019-Dec-30 at 10:32

I have implemented ROI pooling at my graph. The code is as follows.

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ANSWER

Answered 2019-Dec-30 at 10:32

The issue was solved by putting conv layers after RoiPooling.

The first graph was used only for feature extraction using RoiPooling. RoiPooling output size was set bigger dimensions. Then those outputs were used as inputs to the second graph. There conv layers were placed. So that I have weights to optimize.

The modified graph is shown below.

Source https://stackoverflow.com/questions/59516770

QUESTION

coverting roi pooling in pytorch to nn layer

Asked 2018-Nov-05 at 18:29

I have a an mlmodel using ROI pooling for which I am using this (adapted from here) (non NN layer version)

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ANSWER

Answered 2018-Nov-05 at 18:29

Found the issue - The rois after multiplication with spatial scale were being rounded down and had to call round function before calling long like so

Source https://stackoverflow.com/questions/53157978

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install roi_pooling

You can download it from GitHub.
You can use roi_pooling like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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